Details of (2,3,) -related L-R pairs
(2,3,:) Pattern
(2,3,) -related L-R pairs (Top6 pairs)
library("scTensor")
load("reanalysis.RData")
col <- .setColor("many")[1]
scTensor:::.myvisNetwork(g, col)| Rank | Ligand Gene | Receptor Gene | Ligand Expression (Log10(exp + 1)) | Receptor Expression (Log10(exp + 1)) | LR-pair factor value (Percentage) | P-value (Grubbs test) | Q-value (BH method) | PubMed |
|---|---|---|---|---|---|---|---|---|
| 1 | SPARCL1 Description: SPARC like 1 GO: 1-13 Reactome: 1-4 UniProtKB: 1-4 STRING: RefEx: SPARCL1 Expression Atlas: SPARCL1 Single Cell Expression Atlas: SPARCL1 scRNASeqDB: SPARCL1 PanglaoDB: SPARCL1 CMap: SPARCL1 MeSH: 1-93 94-186 187-279 280-369 |
APLNR Description: apelin receptor GO: 1-20 Reactome: 1-7 UniProtKB: 1-3 STRING: RefEx: APLNR Expression Atlas: APLNR Single Cell Expression Atlas: APLNR scRNASeqDB: APLNR PanglaoDB: APLNR CMap: APLNR MeSH: 1-91 92-182 183-273 274-364 365-455 456-546 547-632 |
 |
 |
0.558 (8.493%) | 0.007 | 0.026 | 1-11 |
| 2 | CXCL10 Description: C-X-C motif chemokine ligand 10 GO: 1-48 Reactome: 1-12 UniProtKB: 1-2 STRING: 1 RefEx: CXCL10 Expression Atlas: CXCL10 Single Cell Expression Atlas: CXCL10 scRNASeqDB: CXCL10 PanglaoDB: CXCL10 CMap: CXCL10 MeSH: 1-99 100-198 199-297 298-396 397-495 496-594 595-693 694-792 793-891 892-990 991-1089 1090-1188 1189-1287 1288-1386 1387-1485 1486-1584 1585-1683 1684-1782 1783-1881 1882-1966 |
APLNR Description: apelin receptor GO: 1-20 Reactome: 1-7 UniProtKB: 1-3 STRING: RefEx: APLNR Expression Atlas: APLNR Single Cell Expression Atlas: APLNR scRNASeqDB: APLNR PanglaoDB: APLNR CMap: APLNR MeSH: 1-91 92-182 183-273 274-364 365-455 456-546 547-632 |
 |
|
0.443 (6.741%) | 0 | 0.001 | 1-20 |
| 3 | CXCL10 Description: C-X-C motif chemokine ligand 10 GO: 1-48 Reactome: 1-12 UniProtKB: 1-2 STRING: 1 RefEx: CXCL10 Expression Atlas: CXCL10 Single Cell Expression Atlas: CXCL10 scRNASeqDB: CXCL10 PanglaoDB: CXCL10 CMap: CXCL10 MeSH: 1-99 100-198 199-297 298-396 397-495 496-594 595-693 694-792 793-891 892-990 991-1089 1090-1188 1189-1287 1288-1386 1387-1485 1486-1584 1585-1683 1684-1782 1783-1881 1882-1966 |
PTGER3 Description: prostaglandin E receptor 3 GO: 1-14 Reactome: 1-8 UniProtKB: 1-2 STRING: RefEx: PTGER3 Expression Atlas: PTGER3 Single Cell Expression Atlas: PTGER3 scRNASeqDB: PTGER3 PanglaoDB: PTGER3 CMap: PTGER3 MeSH: 1-90 91-180 181-270 271-360 361-450 451-540 541-630 631-718 |
|
 |
0.394 (6.003%) | 0 | 0 | 1-28 |
| 4 | IGF1 Description: insulin like growth factor 1 GO: 1-82 Reactome: 1-14 UniProtKB: 1-4 STRING: RefEx: IGF1 Expression Atlas: IGF1 Single Cell Expression Atlas: IGF1 scRNASeqDB: IGF1 PanglaoDB: IGF1 CMap: IGF1 MeSH: 1-98 99-196 197-294 295-392 393-490 491-588 589-686 687-784 785-882 883-980 981-1078 1079-1176 1177-1274 1275-1372 1373-1470 1471-1568 1569-1666 1667-1764 1765-1862 1863-1960 1961-2058 2059-2156 2157-2254 2255-2352 2353-2450 2451-2548 2549-2646 2647-2744 2745-2842 2843-2940 2941-3038 3039-3136 3137-3226 |
APLNR Description: apelin receptor GO: 1-20 Reactome: 1-7 UniProtKB: 1-3 STRING: RefEx: APLNR Expression Atlas: APLNR Single Cell Expression Atlas: APLNR scRNASeqDB: APLNR PanglaoDB: APLNR CMap: APLNR MeSH: 1-91 92-182 183-273 274-364 365-455 456-546 547-632 |
 |
|
0.297 (4.514%) | 1 | 1 | 1-30 |
| 5 | SPARCL1 Description: SPARC like 1 GO: 1-13 Reactome: 1-4 UniProtKB: 1-4 STRING: RefEx: SPARCL1 Expression Atlas: SPARCL1 Single Cell Expression Atlas: SPARCL1 scRNASeqDB: SPARCL1 PanglaoDB: SPARCL1 CMap: SPARCL1 MeSH: 1-93 94-186 187-279 280-369 |
NTRK2 Description: neurotrophic receptor tyrosine kinase 2 GO: 1-67 Reactome: 1-17 UniProtKB: 1-4 STRING: RefEx: NTRK2 Expression Atlas: NTRK2 Single Cell Expression Atlas: NTRK2 scRNASeqDB: NTRK2 PanglaoDB: NTRK2 CMap: NTRK2 MeSH: 1-94 95-188 189-282 283-376 377-470 471-564 565-658 659-752 753-846 847-940 941-1034 1035-1127 |
|
 |
0.274 (4.175%) | 0.004 | 0.019 | 1-22 |
| 6 | ANGPT2 Description: angiopoietin 2 GO: 1-29 Reactome: 1-3 UniProtKB: 1-1 STRING: RefEx: ANGPT2 Expression Atlas: ANGPT2 Single Cell Expression Atlas: ANGPT2 scRNASeqDB: ANGPT2 PanglaoDB: ANGPT2 CMap: ANGPT2 MeSH: 1-94 95-188 189-282 283-376 377-470 471-564 565-658 659-752 753-846 847-940 941-1034 1035-1128 1129-1222 1223-1312 |
NTRK2 Description: neurotrophic receptor tyrosine kinase 2 GO: 1-67 Reactome: 1-17 UniProtKB: 1-4 STRING: RefEx: NTRK2 Expression Atlas: NTRK2 Single Cell Expression Atlas: NTRK2 scRNASeqDB: NTRK2 PanglaoDB: NTRK2 CMap: NTRK2 MeSH: 1-94 95-188 189-282 283-376 377-470 471-564 565-658 659-752 753-846 847-940 941-1034 1035-1127 |
 |
|
0.257 (3.908%) | 0.356 | 0.879 | 1-29 |
(2,3,) -related Enrichment Analysis
load("reanalysis.RData")
library("plotly")## Loading required package: ggplot2##
## Attaching package: 'plotly'## The following object is masked from 'package:ggplot2':
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## last_plot## The following object is masked from 'package:AnnotationDbi':
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## select## The following object is masked from 'package:MeSHDbi':
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## select## The following object is masked from 'package:LRBaseDbi':
##
## select## The following object is masked from 'package:IRanges':
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## slice## The following object is masked from 'package:S4Vectors':
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## rename## The following object is masked from 'package:stats':
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## filter## The following object is masked from 'package:graphics':
##
## layoutGO-Enrichment Analysis (BP : Biological Process)
negLogPval <- -log10(out.vecLR[['pattern_2_3']]$Enrich$GO_BP$Pvalue + 1E-10)
term <- out.vecLR[['pattern_2_3']]$Enrich$GO_BP$Term
target <- seq_len(min(100, length(negLogPval)))
negLogPval <- negLogPval[target]
term <- term[target]
p <- plot_ly(x=seq_along(negLogPval), y=~negLogPval,
type="bar", color=~negLogPval, text=term,
colors=c("#4b61ba", "gray", "#a87963", "red"))
layout(p, title="GO-Enrichment Analysis (BP)",
xaxis=list(title="Term"),
yaxis=list(title="-Log(P-value)"),
legend=list(name=""))## Warning: `arrange_()` is deprecated as of dplyr 0.7.0.
## Please use `arrange()` instead.
## See vignette('programming') for more help
## [90mThis warning is displayed once every 8 hours.[39m
## [90mCall `lifecycle::last_warnings()` to see where this warning was generated.[39m## Warning: textfont.color doesn't (yet) support data arrays
## Warning: textfont.color doesn't (yet) support data arrays
GO-Enrichment Analysis (MF : Molecular Function)
negLogPval <- -log10(out.vecLR[['pattern_2_3']]$Enrich$GO_MF$Pvalue + 1E-10)
term <- out.vecLR[['pattern_2_3']]$Enrich$GO_MF$Term
target <- seq_len(min(100, length(negLogPval)))
negLogPval <- negLogPval[target]
term <- term[target]
p <- plot_ly(x=seq_along(negLogPval), y=~negLogPval,
type="bar", color=~negLogPval, text=term,
colors=c("#4b61ba", "gray", "#a87963", "red"))
layout(p, title="GO-Enrichment Analysis (MF)",
xaxis=list(title="Term"),
yaxis=list(title="-Log(P-value)"),
legend=list(name=""))
GO-Enrichment Analysis (CC : Cellular Component)
negLogPval <- -log10(out.vecLR[['pattern_2_3']]$Enrich$GO_CC$Pvalue + 1E-10)
term <- out.vecLR[['pattern_2_3']]$Enrich$GO_CC$Term
target <- seq_len(min(100, length(negLogPval)))
negLogPval <- negLogPval[target]
term <- term[target]
p <- plot_ly(x=seq_along(negLogPval), y=~negLogPval,
type="bar", color=~negLogPval, text=term,
colors=c("#4b61ba", "gray", "#a87963", "red"))
layout(p, title="GO-Enrichment Analysis (CC)",
xaxis=list(title="Term"),
yaxis=list(title="-Log(P-value)"),
legend=list(name=""))
MeSH-Enrichment Analysis (A : Anatomy)
negLogPval <- -log10(out.vecLR[['pattern_2_3']]$Enrich$MeSH_A$Pvalue + 1E-10)
term <- out.vecLR[['pattern_2_3']]$Enrich$MeSH_A$Term
target <- seq_len(min(100, length(negLogPval)))
negLogPval <- negLogPval[target]
term <- term[target]
p <- plot_ly(x=seq_along(negLogPval), y=~negLogPval,
type="bar", color=~negLogPval, text=term,
colors=c("#4b61ba", "gray", "#a87963", "red"))
layout(p, title="MeSH-Enrichment Analysis (A)",
xaxis=list(title="Term"),
yaxis=list(title="-Log(P-value)"),
legend=list(name=""))
MeSH-Enrichment Analysis (B : Organisms)
negLogPval <- -log10(out.vecLR[['pattern_2_3']]$Enrich$MeSH_B$Pvalue + 1E-10)
term <- out.vecLR[['pattern_2_3']]$Enrich$MeSH_B$Term
target <- seq_len(min(100, length(negLogPval)))
negLogPval <- negLogPval[target]
term <- term[target]
p <- plot_ly(x=seq_along(negLogPval), y=~negLogPval,
type="bar", color=~negLogPval, text=term,
colors=c("#4b61ba", "gray", "#a87963", "red"))
layout(p, title="MeSH-Enrichment Analysis (B)",
xaxis=list(title="Term"),
yaxis=list(title="-Log(P-value)"),
legend=list(name=""))
MeSH-Enrichment Analysis (C : Diseases)
negLogPval <- -log10(out.vecLR[['pattern_2_3']]$Enrich$MeSH_C$Pvalue + 1E-10)
term <- out.vecLR[['pattern_2_3']]$Enrich$MeSH_C$Term
target <- seq_len(min(100, length(negLogPval)))
negLogPval <- negLogPval[target]
term <- term[target]
p <- plot_ly(x=seq_along(negLogPval), y=~negLogPval,
type="bar", color=~negLogPval, text=term,
colors=c("#4b61ba", "gray", "#a87963", "red"))
layout(p, title="MeSH-Enrichment Analysis (C)",
xaxis=list(title="Term"),
yaxis=list(title="-Log(P-value)"),
legend=list(name=""))
MeSH-Enrichment Analysis (D : Drugs)
negLogPval <- -log10(out.vecLR[['pattern_2_3']]$Enrich$MeSH_D$Pvalue + 1E-10)
term <- out.vecLR[['pattern_2_3']]$Enrich$MeSH_D$Term
target <- seq_len(min(100, length(negLogPval)))
negLogPval <- negLogPval[target]
term <- term[target]
p <- plot_ly(x=seq_along(negLogPval), y=~negLogPval,
type="bar", color=~negLogPval, text=term,
colors=c("#4b61ba", "gray", "#a87963", "red"))
layout(p, title="MeSH-Enrichment Analysis (D)",
xaxis=list(title="Term"),
yaxis=list(title="-Log(P-value)"),
legend=list(name=""))
MeSH-Enrichment Analysis (E : Analytical, Diagnostic and Therapeutic Techniques and Equipment)
negLogPval <- -log10(out.vecLR[['pattern_2_3']]$Enrich$MeSH_E$Pvalue + 1E-10)
term <- out.vecLR[['pattern_2_3']]$Enrich$MeSH_E$Term
target <- seq_len(min(100, length(negLogPval)))
negLogPval <- negLogPval[target]
term <- term[target]
p <- plot_ly(x=seq_along(negLogPval), y=~negLogPval,
type="bar", color=~negLogPval, text=term,
colors=c("#4b61ba", "gray", "#a87963", "red"))
layout(p, title="MeSH-Enrichment Analysis (E)",
xaxis=list(title="Term"),
yaxis=list(title="-Log(P-value)"),
legend=list(name=""))
MeSH-Enrichment Analysis (F : Psychiatry and Psychology)
negLogPval <- -log10(out.vecLR[['pattern_2_3']]$Enrich$MeSH_F$Pvalue + 1E-10)
term <- out.vecLR[['pattern_2_3']]$Enrich$MeSH_F$Term
target <- seq_len(min(100, length(negLogPval)))
negLogPval <- negLogPval[target]
term <- term[target]
p <- plot_ly(x=seq_along(negLogPval), y=~negLogPval,
type="bar", color=~negLogPval, text=term,
colors=c("#4b61ba", "gray", "#a87963", "red"))
layout(p, title="MeSH-Enrichment Analysis (F)",
xaxis=list(title="Term"),
yaxis=list(title="-Log(P-value)"),
legend=list(name=""))
MeSH-Enrichment Analysis (G : Phenomena and Processes)
negLogPval <- -log10(out.vecLR[['pattern_2_3']]$Enrich$MeSH_G$Pvalue + 1E-10)
term <- out.vecLR[['pattern_2_3']]$Enrich$MeSH_G$Term
target <- seq_len(min(100, length(negLogPval)))
negLogPval <- negLogPval[target]
term <- term[target]
p <- plot_ly(x=seq_along(negLogPval), y=~negLogPval,
type="bar", color=~negLogPval, text=term,
colors=c("#4b61ba", "gray", "#a87963", "red"))
layout(p, title="MeSH-Enrichment Analysis (G)",
xaxis=list(title="Term"),
yaxis=list(title="-Log(P-value)"),
legend=list(name=""))
MeSH-Enrichment Analysis (H : Disciplines and Occupations)
negLogPval <- -log10(out.vecLR[['pattern_2_3']]$Enrich$MeSH_H$Pvalue + 1E-10)
term <- out.vecLR[['pattern_2_3']]$Enrich$MeSH_H$Term
target <- seq_len(min(100, length(negLogPval)))
negLogPval <- negLogPval[target]
term <- term[target]
p <- plot_ly(x=seq_along(negLogPval), y=~negLogPval,
type="bar", color=~negLogPval, text=term,
colors=c("#4b61ba", "gray", "#a87963", "red"))
layout(p, title="MeSH-Enrichment Analysis (H)",
xaxis=list(title="Term"),
yaxis=list(title="-Log(P-value)"),
legend=list(name=""))
MeSH-Enrichment Analysis (I : Anthropology, Education, Sociology and Social Phenomena)
negLogPval <- -log10(out.vecLR[['pattern_2_3']]$Enrich$MeSH_I$Pvalue + 1E-10)
term <- out.vecLR[['pattern_2_3']]$Enrich$MeSH_I$Term
target <- seq_len(min(100, length(negLogPval)))
negLogPval <- negLogPval[target]
term <- term[target]
p <- plot_ly(x=seq_along(negLogPval), y=~negLogPval,
type="bar", color=~negLogPval, text=term,
colors=c("#4b61ba", "gray", "#a87963", "red"))
layout(p, title="MeSH-Enrichment Analysis (I)",
xaxis=list(title="Term"),
yaxis=list(title="-Log(P-value)"),
legend=list(name=""))
MeSH-Enrichment Analysis (J : Technology and Food and Beverages)
negLogPval <- -log10(out.vecLR[['pattern_2_3']]$Enrich$MeSH_J$Pvalue + 1E-10)
term <- out.vecLR[['pattern_2_3']]$Enrich$MeSH_J$Term
target <- seq_len(min(100, length(negLogPval)))
negLogPval <- negLogPval[target]
term <- term[target]
p <- plot_ly(x=seq_along(negLogPval), y=~negLogPval,
type="bar", color=~negLogPval, text=term,
colors=c("#4b61ba", "gray", "#a87963", "red"))
layout(p, title="MeSH-Enrichment Analysis (J)",
xaxis=list(title="Term"),
yaxis=list(title="-Log(P-value)"),
legend=list(name=""))
MeSH-Enrichment Analysis (K : Humanities)
negLogPval <- -log10(out.vecLR[['pattern_2_3']]$Enrich$MeSH_K$Pvalue + 1E-10)
term <- out.vecLR[['pattern_2_3']]$Enrich$MeSH_K$Term
target <- seq_len(min(100, length(negLogPval)))
negLogPval <- negLogPval[target]
term <- term[target]
p <- plot_ly(x=seq_along(negLogPval), y=~negLogPval,
type="bar", color=~negLogPval, text=term,
colors=c("#4b61ba", "gray", "#a87963", "red"))
layout(p, title="MeSH-Enrichment Analysis (K)",
xaxis=list(title="Term"),
yaxis=list(title="-Log(P-value)"),
legend=list(name=""))
MeSH-Enrichment Analysis (L : Information Science)
negLogPval <- -log10(out.vecLR[['pattern_2_3']]$Enrich$MeSH_L$Pvalue + 1E-10)
term <- out.vecLR[['pattern_2_3']]$Enrich$MeSH_L$Term
target <- seq_len(min(100, length(negLogPval)))
negLogPval <- negLogPval[target]
term <- term[target]
p <- plot_ly(x=seq_along(negLogPval), y=~negLogPval,
type="bar", color=~negLogPval, text=term,
colors=c("#4b61ba", "gray", "#a87963", "red"))
layout(p, title="MeSH-Enrichment Analysis (L)",
xaxis=list(title="Term"),
yaxis=list(title="-Log(P-value)"),
legend=list(name=""))
MeSH-Enrichment Analysis (M : Persons)
negLogPval <- -log10(out.vecLR[['pattern_2_3']]$Enrich$MeSH_M$Pvalue + 1E-10)
term <- out.vecLR[['pattern_2_3']]$Enrich$MeSH_M$Term
target <- seq_len(min(100, length(negLogPval)))
negLogPval <- negLogPval[target]
term <- term[target]
p <- plot_ly(x=seq_along(negLogPval), y=~negLogPval,
type="bar", color=~negLogPval, text=term,
colors=c("#4b61ba", "gray", "#a87963", "red"))
layout(p, title="MeSH-Enrichment Analysis (M)",
xaxis=list(title="Term"),
yaxis=list(title="-Log(P-value)"),
legend=list(name=""))
MeSH-Enrichment Analysis (N : Health Care)
negLogPval <- -log10(out.vecLR[['pattern_2_3']]$Enrich$MeSH_N$Pvalue + 1E-10)
term <- out.vecLR[['pattern_2_3']]$Enrich$MeSH_N$Term
target <- seq_len(min(100, length(negLogPval)))
negLogPval <- negLogPval[target]
term <- term[target]
p <- plot_ly(x=seq_along(negLogPval), y=~negLogPval,
type="bar", color=~negLogPval, text=term,
colors=c("#4b61ba", "gray", "#a87963", "red"))
layout(p, title="MeSH-Enrichment Analysis (N)",
xaxis=list(title="Term"),
yaxis=list(title="-Log(P-value)"),
legend=list(name=""))
MeSH-Enrichment Analysis (V : Publication Type)
negLogPval <- -log10(out.vecLR[['pattern_2_3']]$Enrich$MeSH_V$Pvalue + 1E-10)
term <- out.vecLR[['pattern_2_3']]$Enrich$MeSH_V$Term
target <- seq_len(min(100, length(negLogPval)))
negLogPval <- negLogPval[target]
term <- term[target]
p <- plot_ly(x=seq_along(negLogPval), y=~negLogPval,
type="bar", color=~negLogPval, text=term,
colors=c("#4b61ba", "gray", "#a87963", "red"))
layout(p, title="MeSH-Enrichment Analysis (V)",
xaxis=list(title="Term"),
yaxis=list(title="-Log(P-value)"),
legend=list(name=""))
MeSH-Enrichment Analysis (Z : Geographical Locations)
negLogPval <- -log10(out.vecLR[['pattern_2_3']]$Enrich$MeSH_Z$Pvalue + 1E-10)
term <- out.vecLR[['pattern_2_3']]$Enrich$MeSH_Z$Term
target <- seq_len(min(100, length(negLogPval)))
negLogPval <- negLogPval[target]
term <- term[target]
p <- plot_ly(x=seq_along(negLogPval), y=~negLogPval,
type="bar", color=~negLogPval, text=term,
colors=c("#4b61ba", "gray", "#a87963", "red"))
layout(p, title="MeSH-Enrichment Analysis (Z)",
xaxis=list(title="Term"),
yaxis=list(title="-Log(P-value)"),
legend=list(name=""))
Reactome Pathway-Enrichment Analysis
negLogPval <- -log10(out.vecLR[['pattern_2_3']]$Enrich$Reactome$Pvalue + 1E-10)
term <- out.vecLR[['pattern_2_3']]$Enrich$Reactome$Term
target <- seq_len(min(100, length(negLogPval)))
negLogPval <- negLogPval[target]
term <- term[target]
p <- plot_ly(x=seq_along(negLogPval), y=~negLogPval,
type="bar", color=~negLogPval, text=term,
colors=c("#4b61ba", "gray", "#a87963", "red"))
layout(p, title="Reactome-Enrichment Analysis",
xaxis=list(title="Term"),
yaxis=list(title="-Log(P-value)"),
legend=list(name=""))
DO-Enrichment Analysis
negLogPval <- -log10(out.vecLR[['pattern_2_3']]$Enrich$DO$Pvalue + 1E-10)
term <- out.vecLR[['pattern_2_3']]$Enrich$DO$Term
target <- seq_len(min(100, length(negLogPval)))
negLogPval <- negLogPval[target]
term <- term[target]
p <- plot_ly(x=seq_along(negLogPval), y=~negLogPval,
type="bar", color=~negLogPval, text=term,
colors=c("#4b61ba", "gray", "#a87963", "red"))
layout(p, title="DO-Enrichment Analysis",
xaxis=list(title="Term"),
yaxis=list(title="-Log(P-value)"),
legend=list(name=""))
NCG-Enrichment Analysis
negLogPval <- -log10(out.vecLR[['pattern_2_3']]$Enrich$NCG$Pvalue + 1E-10)
term <- out.vecLR[['pattern_2_3']]$Enrich$NCG$Term
target <- seq_len(min(100, length(negLogPval)))
negLogPval <- negLogPval[target]
term <- term[target]
p <- plot_ly(x=seq_along(negLogPval), y=~negLogPval,
type="bar", color=~negLogPval, text=term,
colors=c("#4b61ba", "gray", "#a87963", "red"))
layout(p, title="NCG-Enrichment Analysis",
xaxis=list(title="Term"),
yaxis=list(title="-Log(P-value)"),
legend=list(name=""))
DGN-Enrichment Analysis
negLogPval <- -log10(out.vecLR[['pattern_2_3']]$Enrich$DGN$Pvalue + 1E-10)
term <- out.vecLR[['pattern_2_3']]$Enrich$DGN$Term
target <- seq_len(min(100, length(negLogPval)))
negLogPval <- negLogPval[target]
term <- term[target]
p <- plot_ly(x=seq_along(negLogPval), y=~negLogPval,
type="bar", color=~negLogPval, text=term,
colors=c("#4b61ba", "gray", "#a87963", "red"))
layout(p, title="DGN-Enrichment Analysis",
xaxis=list(title="Term"),
yaxis=list(title="-Log(P-value)"),
legend=list(name=""))